Validation of meteorological data

The performance of meteorological data is characterized by comparison with good quality ground measurements from weather stations. Bias or Mean Bias Deviation (MBD) characterizes systematic model deviations at a given site, i.e. systematic over- or underestimation: bias values will be above zero when satellite modelled values are overestimating and below zero when underestimating (in comparison to ground measurements).

A validation procedure was carried out to compare the modelled data from the Solargis database with ground-measured data from the meteorological stations available through NOAA Integrated Surface Database (ISD) network. In the comparison 11,516 stations were used and the compared data period was going from 2006 to 2015.

The validation of meteorological information provided in Solargis data deliveries are presented for three parameters: Temperature at 2 metres, Wind Speed at 10 metres and Relative Humidity. The validation statistics of these three parameters show good results in terms of accuracy: average bias close to zero and low standard deviation of bias. Aggregated results are shown in the table and individual statistics are represented in the maps below.

It should be noted that in general data from the meteorological models represent a larger area, and they are not capable of accurately representing the local microclimates, especially in mountainous and coastal zones. This also means that complex areas with lot of contrast are more prone to see higher deviations. Areas with limited availability of data from weather stations, which are used as an input for the NWP models, would be also prone to show such differences. In addition, very extreme weather phenomena cannot be estimated with high precision using modelled data.

From the validation results represented in the maps below we can see this behaviour. Places with higher bias between measured and modelled data are typically located next to mountain areas, coast places and in general areas where the landscape and microclimatic conditions changes more intensively and less gradually. Looking at the bias statistics, it is also to be noted that the deviations during night-time are usually higher, i.e. the values provided during the solar power generation hours are in general estimated with lower uncertainty.

A correct evaluation and interpretation of uncertainty is very much related to expert decision making based on the knowledge collected from the experience in working with the data. If available, the use of ground measured data next to the project site is recommended for performing site-adaptation, i.e. correlation of the data by comparing the modelled data with the ground measured data. This procedure would allow correcting these deviations and improve the accuracy of the modelled data for that specific site.

Validation statistics for temperature, wind speed and relative humidity data provided in Solargis. Aggregated results across the 11,516 stations.

Map of global all-day air temperature at 2 m bias distribution

Map of global all-day wind speed bias distribution

Map of global all-day relative humidity bias distribution